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validate-json

Check whether a body is valid JSON. The body is discarded.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoHTTPS URL to normalize or cite
hostNoPublic hostname
jsonNoJSON text to validate; discarded after the check
zoneNoIANA timezone name

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

C2.9/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds a genuinely useful trait — 'The body is discarded' — signaling the input is not retained. But it does not disclose the return format, what happens on invalid JSON, or whether this is a pure read operation, which is material for a validation tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences with the purpose front-loaded and the behavioral note second. Every word earns its place, with zero filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple validation tool the description nearly suffices, but the schema's three unrelated parameters (url, host, zone) are unexplained, there is no output schema, and no annotations. An agent has no way to know why those parameters are accepted or what the check returns, leaving an important gap in context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Although schema coverage is 100% (baseline 3), the schema descriptions are misleading: 'url' says 'HTTPS URL to normalize or cite', 'host' says 'Public hostname', and 'zone' says 'IANA timezone name' — all clearly copy-pasted from unrelated sibling tools. The description does not clarify this mismatch or reconcile its term 'body' with the schema's 'json' parameter, so it fails to add value over the schema and actually leaves the agent confused.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('Check') and resource ('whether a body is valid JSON'), which clearly distinguishes it from its sibling tools, none of which do JSON validation. However, the input schema lists parameters (url, host, zone) that are clearly copied from sibling tools like normalize-url and timezone and bear no relation to JSON validation, muddying what 'body' actually refers to.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this tool versus alternatives, no exclusions, and no context about its role among the sibling tools. The description leaves the agent to infer the usage scenario entirely.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

C2.5/5.0
Disambiguation3/5

Some tools overlap in purpose, such as 'citation' and 'normalize-url' both analyzing URLs, and 'compatibility' and 'status-catalog' both dealing with HTTP statuses. However, each has a distinct focus (scheme/status vs. origin/path; classification vs. catalog), so they are not fully redundant.

Naming Consistency5/5

All tool names follow a consistent kebab-case pattern with clear verb-noun or noun-only structures (e.g., 'normalize-url', 'inspect-robots', 'validate-json'). No mixed conventions or irregular naming.

Tool Count5/5

With 11 tools, the set is well-sized for a utility collection covering URL, HTTP, JSON, time, and language functions. It is within the typical 3-15 range and does not feel bloated or sparse.

Completeness3/5

The tools cover a diverse set of standalone web/REST utilities, but there is no cohesive domain or lifecycle (e.g., no CRUD operations, no clear workflow). Some areas could be missing (e.g., DNS lookup, header inspection), but each tool is self-contained for its stated purpose.